AI Article Synopsis

  • Chemical networks have complex, emergent properties that can't be predicted from their individual parts, making their study critical in Systems Chemistry.
  • Research focuses on understanding how these properties might have contributed to prebiotic chemical networks, which are important for the origin and early evolution of life.
  • Using RAF theory, the study examines factors like network modularity, initial seeding, and product inhibition to understand their effects on network dynamics and their implications for experimental design and origin of life theories.

Article Abstract

Chemical networks often exhibit emergent, systems-level properties that cannot be simply derived from the linear sum of the individual components. The design and analysis of increasingly complex chemical networks thus constitute a major area of research in Systems Chemistry. In particular, much research is focused on the emergence of functional properties in prebiotic chemical networks relevant to the origin and early evolution of life. Here, we apply a formal framework known as RAF theory to study the dynamics of a complex network of mutually catalytic peptides. We investigate in detail the influence of network modularity, initial template seeding, and product inhibition on the network dynamics. We show that these results can be useful for designing new experiments, and further argue how they are relevant to origin of life studies.

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Source
http://dx.doi.org/10.1002/cphc.201800101DOI Listing

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